Stefan Hegselmann
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Health Information Management top 10%
- Artificial Intelligence in Healthcare
- Electronic Health Records Systems
Papers in
-
- Semantic Web and Ontologies 3
- Machine Learning in Healthcare 2
- Natural Language Processing Techniques 2
- Explainable Artificial Intelligence (XAI) 1
-
- Biomedical Text Mining and Ontologies 3
- Co-authors
- David Sontag (1 shared paper)Hunter Lang (1 shared paper)Yoon Kim (1 shared paper)Monica Agrawal (1 shared paper)Julian Varghese (6 shared papers)Martin Dugas (12 shared papers)Sarah Sandmann (1 shared paper)Benjamin Wild (2 shared papers)
- Journals
- Nature Communications (1 paper)Nature Medicine (1 paper)Clinical Epidemiology (1 paper)Methods of Information in Medicine (1 paper)BMC Medical Informatics and Decision Making (1 paper)
- Partner nations
- GermanyChinaUnited States
In The Last Decade
Stefan Hegselmann
17 papers receiving 265 citations
Stefan Hegselmann's Hit Papers
Peers
Comparison fields: 5 of 69
- Health Informatics 41
- Health Information Management 20
- Artificial Intelligence 107
- Family Practice 4
- Geriatrics and Gerontology 3
Countries citing papers authored by Stefan Hegselmann
This map shows the geographic impact of Stefan Hegselmann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stefan Hegselmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Hegselmann more than expected).
Fields of papers citing papers by Stefan Hegselmann
This network shows the impact of papers produced by Stefan Hegselmann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stefan Hegselmann. The network helps show where Stefan Hegselmann may publish in the future.
Co-authors
The 25 scholars most cited alongside Stefan Hegselmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Large language models are few-shot clinical information extractors Hit paper breakdown → | 2022 | 161 |
| 2 | Benchmark evaluation of DeepSeek large language models in clinical decision-making Hit paper breakdown → | 2025 | 46 |
| 3 | 2022 | 9 | |
| 4 | 2021 | 9 | |
| 5 | 2018 | 8 | |
| 6 | 2017 | 5 | |
| 7 | 2018 | 5 | |
| 8 | 2019 | 5 | |
| 9 | 2025 | 4 | |
| 10 | 2021 | 4 | |
| 11 | 2018 | 4 | |
| 12 | An Evaluation of the Doctor-Interpretability of Generalized Additive Models with Interactions. | 2020 | 4 |
| 13 | Inverted HMM - a Proof of Concept | 2016 | 3 |
| 14 | Reproducible Survival Prediction with SEER Cancer Data | 2018 | 3 |
| 15 | 2019 | 3 | |
| 16 | 2017 | 3 | |
| 17 | 2016 | 2 | |
| 18 | 2024 | 0 |
About Stefan Hegselmann
Stefan Hegselmann is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems and Management, Health Information Management and Information Systems, having authored 18 papers that have together received 278 indexed citations. Recurring topics across this work include Scientific Computing and Data Management (4 papers), Semantic Web and Ontologies (3 papers), Biomedical Text Mining and Ontologies (3 papers), Machine Learning in Healthcare (2 papers), Natural Language Processing Techniques (2 papers), Electronic Health Records Systems (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). The work is most often cited by research in Health Informatics (41 citations), Health Information Management (20 citations), Artificial Intelligence (107 citations), Family Practice (4 citations) and Geriatrics and Gerontology (3 citations). Stefan Hegselmann has collaborated with scholars based in Germany, China and United States. Frequent co-authors include David Sontag, Hunter Lang, Yoon Kim, Monica Agrawal, Julian Varghese, Martin Dugas, Sarah Sandmann, Benjamin Wild, Roland Eils and Philipp Neuhaus. Their work appears in journals such as Nature Communications, Nature Medicine, Clinical Epidemiology, Methods of Information in Medicine and BMC Medical Informatics and Decision Making.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.